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Machine Learning Summer Internship Jobs in Frederick, MD

Digital Infuzion

Internship Opportunities

Rockville, MD · On-site

Program Overview Digital Infuzion's Summer Internship Program is designed for students and recent ... ready machine-learning models to support real-time clinical decision-making. * Data Science & AI ...

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All JobsMachine Learning Summer JobsMachine Learning Summer Internship JobsMachine Learning Summer Internship Jobs in Frederick, MD

Machine Learning Summer Internship information

See Frederick, MD salary details

$25.4K

$42.3K

$87.5K

How much do machine learning summer internship jobs pay per year?

As of Jul 30, 2026, the average yearly pay for machine learning summer internship in Frederick, MD is $42,340.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,300.00 and $45,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Summer Intern, and why are they important?

To thrive as a Machine Learning Summer Intern, you need a solid background in mathematics, statistics, and programming (especially Python), often supported by ongoing coursework in computer science or related fields. Familiarity with machine learning frameworks like TensorFlow or PyTorch, version control systems such as Git, and data analysis tools is typically required. Strong problem-solving skills, curiosity, and teamwork are important soft skills that help interns contribute effectively and learn quickly. These skills and qualities are crucial for applying theoretical knowledge, collaborating on real projects, and adapting to the fast-evolving field of machine learning.

What types of projects can I expect to work on during a Machine Learning Summer Internship?

As a Machine Learning Summer Intern, you can expect to contribute to projects such as data preprocessing, building and evaluating machine learning models, and assisting with the deployment of algorithms into production environments. Interns often work alongside data scientists and engineers on real-world datasets to solve business problems, develop prototypes, or improve existing models. This hands-on experience will help you gain practical skills in using popular ML frameworks and understanding the end-to-end machine learning workflow.

What is the difference between Machine Learning Summer Internship vs Data Science Summer Internship?

AspectMachine Learning Summer InternshipData Science Summer Internship
Required CredentialsBasic programming, math, and machine learning knowledgeProgramming, statistics, and data analysis skills
Work EnvironmentDeveloping ML models, algorithms, and prototypesData analysis, visualization, and reporting
Industry UsageTech companies, AI startups, research labsBusiness, finance, healthcare, tech firms

Both internships involve working with data and require programming skills, but Machine Learning Summer Internships focus on developing algorithms and models, while Data Science Summer Internships emphasize data analysis and insights. The choice depends on your interest in building models versus analyzing data.

What is a Machine Learning Summer Internship?

A Machine Learning Summer Internship is a temporary, typically 8-12 week program for students or recent graduates to gain practical experience in machine learning. Interns work under the supervision of experienced professionals, contributing to real-world projects involving data analysis, model development, and algorithm implementation. These internships often provide mentorship, networking opportunities, and exposure to the latest tools and technologies in the field. They are valuable for building technical skills and improving career prospects in artificial intelligence and data science.
What are popular job titles related to Machine Learning Summer Internship jobs in Frederick, MD? For Machine Learning Summer Internship jobs in Frederick, MD, the most frequently searched job titles are:
What job categories do people searching Machine Learning Summer Internship jobs in Frederick, MD look for? The top searched job categories for Machine Learning Summer Internship jobs in Frederick, MD are:
What cities near Frederick, MD are hiring for Machine Learning Summer Internship jobs? Cities near Frederick, MD with the most Machine Learning Summer Internship job openings:
Machine Learning Summer Internship jobs near you
Infographic showing various Machine Learning Summer Internship job openings in Frederick, MD as of July 2026, with employment types broken down into 10% Internship, 2% As Needed, 74% Full Time, 12% Part Time, 1% Temporary, and 1% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $42,340 per year, or $20.4 per hour.

Internship Opportunities

Digital Infuzion

Rockville, MD • On-site

Full-time, Internship

Re-posted 8 days ago

Job description

Program Overview
Digital Infuzion's Summer Internship Program is designed for students and recent graduates who want to apply their skills to projects that directly improve public health. Interns gain hands-on experience in biomedical informatics, data science, AI, clinical research, cybersecurity, and business operations-working alongside experts who support the NIH, FDA, and other federal health agencies.
This program is built for candidates who want meaningful work, real professional development, and exposure to mission-driven public health initiatives.
Location
The work schedule for Digital Infuzion is hybrid, and for internships it depends on the internship track, all applicants should be prepared to work a to-be-determined hybrid schedule that would include several days a week in our Rockville, MD office.
What You'll Gain
  • Real Project Experience: Contribute to meaningful, mission-driven assignments that advance healthcare technology.
  • Mentorship: Work closely with seasoned professionals who support your technical and career growth.
  • AI Innovation Challenge: Each summer culminates in a cross-disciplinary AI Innovation Challenge, where interns team up to solve a real-world health IT problem.
  • Networking: Build lasting connections with peers, mentors, and leaders across the company.
  • Growth Path: Many interns successfully transition into full-time careers at Digital Infuzion (DIFZ).

2026 Internship Tracks (Anticipated)
  • Software Development & AI Engineering: Design and build AI-driven applications that support biomedical research and healthcare analytics, leveraging NIH-approved cloud platforms and production-ready machine-learning models to support real-time clinical decision-making.
  • Data Science & AI Research: Apply predictive modeling to improve clinical trial recruitment and diversity, develop NLP pipelines that mine biomedical literature, and craft surveillance models that detect adverse events sooner.
  • Health IT & Biomedical Informatics: Work with NIH clinical research tracking systems (e.g., eRA Commons, NIA CROMS), gain hands-on exposure to FHIR/HL7 interoperability, and tackle data governance and security challenges in health-research IT.
  • Business Operations & GovCon Strategy (Limited Seats): Support proposal writing, contract management, and federal procurement (FAR/DFARS), while contributing to business development efforts for NIH and FDA opportunities.

General Responsibilities (All Interns)
Depending on the track and assignment, interns may:
  • Contribute to project deliverables under the guidance of technical and/or business leaders.
  • Participate in team meetings, mentorship sessions, and professional development activities.
  • Present work progress and outcomes, including participation in the AI Innovation Challenge.
  • Collaborate across disciplines (engineering, data, informatics, operations) to solve real client problems.
  • Produce clear documentation of work (technical notes, analysis, briefs, or proposals, depending on the track).

Required Qualifications
  • U.S. Citizen or U.S. Permanent Resident (mandatory).
  • Currently enrolled in an accredited undergraduate or graduate program.
  • Ability to work on-site from Digital Infuzion headquarters (HQ) in Rockville, MD.
  • Interest in applying skills to public health, healthcare, or health IT mission areas.
  • Strong written and verbal communication skills.
  • Ability to work collaboratively in a professional team environment.

Application Process
To be considered, candidates must submit:
  1. Resume/CV
  2. Statement of Interest (≤ 500 words)
    • Identify your preferred track.
    • Explain why it interests you and how your skills/coursework prepare you to contribute.
  3. Academic Transcript (unofficial PDF or screenshot acceptable)
Upon review of your application, if selected, you will complete a screening call with a member of the Talent Acquisition team to assess overall fit, answer questions, and complete a core values assessment (outlined below).
Digital Infuzion Core Values
Our team thrives in a creative, open, and growth-oriented environment, guided by our core values:
  • Outcomes First: Focus on what matters most and make timely, informed decisions.
  • Innovative: Embrace creativity and continuous improvement to drive novel solutions.
  • Radical Candor: Communicate openly and honestly, balancing direct feedback with genuine care.
  • Never Satisfied: Pursue excellence and continuous growth beyond the status quo.
  • Resilient: Adapt and persevere through challenges, turning obstacles into opportunities.

Digital Infuzion does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factor per Federal laws.
We can provide reasonable accommodation to applicants with disabilities. If you need a reasonable accommodation for any part of the application and hiring process, please contact Talent Acquisition at careers@digitalinfuzion.com. The decision on granting reasonable accommodation will be made on a case-by-case basis.

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